1. European Translational Research Information and KM Services (eTRIKS) Prof Yike Guo Department of Computing Imperial College London Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 1

2. Goals & Objectives Objective: – Provision of a sustainable KM Platform and Service to support Private/Public Translational Research (TR) in IMI and beyond – Single access point to standardised curated TR study information Scope: – Cloud Hosting, KM Platform, Data & Service Standards, Analytics, Curation, and Training – Potentially support for any IMI Project involving translational research Budget: €23.98m for 5 years (Oct/2012---Sept/2017) Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 2

3. Partners Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 3 Academia SME

4. ETRIKS Deliverable KM support for IMI (and other PPP) projects – Access to fit-for-purpose, secure, easy-access, standardised TR KM services (for ongoing cross-organisation TR study support) Hosting / installation Training Curation workflow software Data Mgmt software – Single point of access to curated historic TR study data on the cloud – Sustainable, interoperable, collaborative, re-usable, open source TR platform, based on open, agreed standards, used and contributed to by global research community. Development of an active TR analytics & informatics community TR Informatics Standard and Centralized Data Cloud Analytics software Curation support Standards build and coordination KM consultancy

5. eTRIKS : Linking the Two Worlds Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 5 From : Committee on A Framework for Developing a New Taxonomy of Disease

6. eTRIKS Architecture 6 Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe

7. eTRIKS Study Data Management Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 7

8. eTRIKS Curation: Building Contents Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 8

9. eTRIKS Data Curation Process Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 9 tranSMART-based eTRIKS Study Data Management System

10. U-BIOPRED (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes) Use cases 10 Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 1. Reaching international consensus on diagnostic criteria 2. Creating adult/pediatric cohorts and biobanks 3. Creating novel biology ‘handprints’ by combining molecular, histological, clinical and patient-reported data 4. Validating such ‘handprints’ in relation to exacerbations and disease progression 5. Refining the ‘handprints’ by using preclinical and human exacerbation models 6. Predicting efficacy of gold-standard and novel interventions 7. Refining the diagnostic criteria and phenotypes 8. Establishing a platform for exchange, education and dissemination

11. eTRIKS Ontology Management Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 11

12. Semantic interoperability with Clinical Data Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 12 Electronic Data Capture Software Standard Vocabularies / Libraries eCRF eCRF libraries MML KM Platform

13. Semantic Resources Based on NCBO (BioPortal Ontologies) eTRIKS Possible focus: – UMLS ( Vocabularies include: CPT®, ICD-10-CM, LOINC®, MeSH®, RxNorm, and SNOMED CT®) – CTSA – NCBO Human related Phenotype ontologies – Omics ontologies Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 13

14. Adoption of standards CDISC Data Model – SDTM : Study Data Tabulation Model – ADaM : Analysis Data Model – SEND: Standard for Exchange of Nonclinical Data – CDASH Clinical Data Acquisition Standards Harmonization – PR: Protocol Representation – TDM: Study/Trial Design Model – ODM: Operational Data Model – LAB: Laboratory Data Model – BRIDG Model Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 14

15. Quality assurance of the semantic resources All tools used based on open source community based building Continuous interfacing with developing community and regular standards updates will ensure quality WP3 dedicated to ontologies and standards, led by CDISC Large collaboration with projects across EU/USA Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 15

16. Standards and terminologies selection process Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 16

17. Semantic interoperability issues Legacy data for certain projects / studies – Possible Solution: Development of custom ETL procedures. Diverse EHR systems in clinics : not a problem now but EHR will be an ideal addtion to CTMS – Working closely with projects like EHR4CR/Euroca /Open Phacts Too many standards and mappings – Committing to some widely adopted systems (by IMI projects) Cross projects mapping – Need terminology mapping services : learning Semantic Web technology Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 17

18. Examples Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 18

19. Project Information www.etriks.org Publications – None yet Contact information – Email: y.guo@imperial.ac.uk – Website: http://dsg.doc.ic.ac.ukhttp://dsg.doc.ic.ac.uk Convergence Meeting: Semantic Interoperability for Clinical Research & Patient Safety in Europe 19